A Mobile Context Sharing System Using Activity and Emotion Recognition with Bayesian Networks

With the recent popularization of smart phones, context sharing systems in mobile environment attract attention of people. Mobile context sharing systems can share more information than web-based social network services because they have various sensors. For sharing high-level contexts such as activity and emotion, a user had to manually annotate them in previous works. This paper proposes a mobile context sharing system that can recognize high-level contexts automatically by using Bayesian networks based on collected mobile logs. We have implemented the Context Viewer application which consists of a phonebook and a map browser to prove the feasibility of the proposed system. Also, we have confirmed that the proposed system is useful, by evaluating Bayesian networks and performing the SUS test.